Search Results for "source code computer" - Page 92
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Showing 20596 open source projects for "source code computer"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Google Cloud Platform Node.js Samples
Node.js samples for Google Cloud Platform products
Google Cloud Platform Node.js Samples repository is a large set of Node.js code examples that demonstrate how to build, deploy, and manage applications using Google Cloud Platform services. It mirrors the structure and purpose of the Python and Go sample repositories, providing developers with practical implementations that complement official documentation. The repository includes examples for a wide variety of services, such as Cloud Run, App Engine, storage systems, and APIs, along with... -
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AutoViz
Automatically Visualize any dataset, any size
AutoViz is a Python data visualization library designed to automate exploratory data analysis by generating multiple visualizations with minimal code. The primary goal of the project is to help data scientists and analysts quickly understand patterns, relationships, and anomalies within datasets without manually writing complex plotting code. With a single command, the library can automatically generate dozens of charts and graphs that reveal insights into the structure and quality of the... -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis.... -
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multi-agent-shogun
Samurai-inspired multi-agent system for Claude Code
multi-agent-shogun is a multi-agent orchestration system designed to coordinate multiple AI coding agents working in parallel. Inspired by the hierarchy of a feudal Japanese military structure, the system organizes agents into roles such as Shogun, Karo, and Ashigaru, which correspond to strategist, coordinator, and worker agents. A user interacts primarily with the Shogun agent by issuing natural language instructions that describe the desired tasks. The system then automatically... -
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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ChatJS
Production-ready AI chat. Start here and make it your own
ChatJS is a production-ready AI chat foundation for developers who want to launch customizable chat applications without rebuilding common infrastructure from scratch. The project presents itself as a starting point that already includes authentication, model access, streaming, and tool support so teams can focus on their own product-specific features. Its stack is centered on modern TypeScript web development, using technologies such as Next.js, AI SDK tooling, PostgreSQL, Redis, and... -
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Neuron AI
The PHP Agentic Framework to build production-ready AI driven apps
Neuron AI is a PHP agentic framework for building production-ready AI applications that connect models, memory, vector databases, and tools into working agents. It is designed for developers who want to create systems such as RAG pipelines, multi-agent workflows, and business process automations without having to hand-build every integration from scratch. The framework provides an Agent class that can be extended to inherit core capabilities like memory, tools, function calling, and... -
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AI Agents From Scratch
Demystify AI agents by building them yourself. Local LLMs
AI Agents from Scratch is an educational repository designed to teach developers how to build autonomous AI agents using large language models and modern AI frameworks. The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external... -
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Depth Anything 3
Recovering the Visual Space from Any Views
Depth Anything 3 is a research-driven project that brings accurate and dense depth estimation to any input image or video, enabling foundational understanding of 3D structure from 2D visual content. Designed to work across diverse scenes, lighting conditions, and image types, it uses advanced neural networks trained on large, heterogeneous datasets, producing depth maps that reveal scene depth relationships and object surfaces with strong fidelity. The model can be applied to photography,... -
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mgrep
A calm, CLI-native way to semantically grep everything, like code
This project is a modern, semantic search tool that brings the simplicity of traditional command-line grep to the world of natural language and multimodal content, enabling users to search across codebases, documents, PDFs, and even images using meaning-aware queries. Built with a focus on calm CLI experiences, it lets you index and query your local files with semantic understanding, delivering results that are relevant to your intent rather than simple pattern matches, which is especially... -
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Scanopy
Clean network diagrams, One-time setup, zero upkeep
Scanopy is a powerful multi-modal data capture and analysis toolkit that enables users to collect, process, and visualize structured and unstructured information from a variety of sources in a flexible pipeline. It is built to handle complex scanning tasks — such as OCR, document analysis, audio transcription, network data capture, and image extraction — while providing unified APIs and workflows that make managing heterogeneous data sources seamless. Developers can compose custom pipelines... -
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ML Sharp
Sharp Monocular View Synthesis in Less Than a Second
ML Sharp is a research code release that turns a single 2D photograph into a photorealistic 3D representation that can be rendered from nearby viewpoints. Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to... -
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n-skills
Curated plugin marketplace for AI agents
n-skills is a curated plugin marketplace and universal skills collection for AI coding agents that standardizes how skills are defined, discovered, and installed across multiple frameworks and agent platforms. It organizes skills into categories such as workflow orchestration, tools, automation, and documentation support, making it easy for developers to add capabilities like browser automation, multi-agent workflow coordination, or repo maintenance assistance. The repository includes a... -
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CSS Reference
Fee visual guide to the most popular CSS properties
CSS Reference is a human-friendly, example-driven reference for CSS that focuses on how properties behave in practice rather than only listing their syntax. Each entry explains what a property does, shows concise examples, and illustrates the visual result so you can internalize concepts quickly. The reference highlights common pitfalls and “gotchas,” helping you avoid surprises when mixing layout modes like Flexbox and Grid or when dealing with overflow and positioning. It favors clarity... -
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handson-ml2
Jupyter notebooks that walk you through the fundamentals of ML
This repository contains the Jupyter notebooks and code for the second edition of a popular hands-on machine learning book that teaches both classical ML and deep learning using modern tooling. The notebooks emphasize end-to-end workflows: data preparation, model selection, tuning, and reliable evaluation. Deep learning sections use the contemporary Keras/TensorFlow 2 ecosystem, highlighting clean APIs and eager execution to make experiments easier to reason about. Traditional ML topics... -
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Front-End Performance Checklist
The only Front-End Performance Checklist that runs faster
Front-End-Performance-Checklist is a comprehensive, developer-friendly guide that consolidates the most impactful client-side performance practices into a single, scannable resource. It frames performance as a front-end responsibility and turns broad principles into concrete, verifiable checks you can apply before shipping. The checklist is organized by areas such as HTML, CSS, JavaScript, fonts, images, and network delivery, so teams can tackle bottlenecks systematically. Each section... -
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phpunit/php-timer
Utility class for timing
php-timer is a tiny utility library that provides high-resolution timing for PHP scripts, originating from the PHPUnit ecosystem. It wraps PHP’s underlying timing functions to give consistent start/stop measurements even across different PHP versions and environments. The library’s API is intentionally small so you can drop it into tests, benchmarks, and command-line tools without overhead. Beyond raw seconds, it can format durations into human-readable strings, which is especially handy for... -
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Earth Engine API
Python and JavaScript bindings for calling the Earth Engine API
The Earth Engine API provides Python and JavaScript client libraries for Google Earth Engine, a planetary-scale geospatial analysis platform. With it, users compose lazy, server-side computations over massive catalogs of satellite imagery and vector datasets without handling raw files locally. The API exposes functional operators for map algebra, reducers, joins, and machine learning that scale transparently on Earth Engine’s backend. Developers authenticate once, work interactively in... -
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4M
4M: Massively Multimodal Masked Modeling
4M is a training framework for “any-to-any” vision foundation models that uses tokenization and masking to scale across many modalities and tasks. The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. Training/inference configs and issues discuss things... -
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Phoenix Framework
Peace of mind from prototype to production
Phoenix is a high-performance, productive web development framework written in Elixir. It runs on the Erlang VM (BEAM). It is designed to support both traditional request/response web applications. It also supports real-time, soft-real-time applications via WebSockets, channels, PubSub, and presence features. Phoenix emphasizes fault tolerance, scalability, and developer productivity. It provides tools like code generators, LiveView integration, templating, routing, and a flexible plug... -
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PowerHub
A post exploitation tool based on a web application
PowerHub is a PowerShell-based automation framework designed to centralize and orchestrate common administrative tasks across Windows environments. It exposes a modular command set for inventorying systems, managing services, deploying packages, and executing remote commands with consistent logging and error handling. The project places emphasis on discoverability and reuse: scripts are organized into reusable modules and functions with clear parameter contracts so teams can compose... -
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MooseStack
The developer framework for building analytical backends
MooseStack is an opinionated starter stack that assembles a modern web application foundation—project structure, build tooling, and deployment scripts—so teams can get from “blank repo” to a working product quickly. It provides a coherent layout for server and client code, standardizes environment configuration, and includes scripts to run the app locally with the same conventions you’ll use in staging or production. The stack favors convention over configuration: common decisions around... -
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Remarkable for Linux
The Markdown Editor for Linux
With Live Preview you can see your changes as you make them. There is no need to export first to check your syntax. This is accompanied by synchronized scrolling. Remarkable has Github Flavoured Markdown. This has a simple, easy-to-learn syntax with features like checklists, highlighting, links, images and more. Remarkable allows you to export your files to PDF and HTML from within the app. The HTML code is even prettified and PDFs have a TOC. You can style your markdown documents however... -
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Laravel Echo
Laravel Echo library for beautiful Pusher and Ably integration
In many modern web applications, WebSockets are used to implement realtime, live-updating user interfaces. When some data is updated on the server, a message is typically sent over a WebSocket connection to be handled by the client. This provides a more robust, efficient alternative to continually polling your application for changes. To assist you in building these types of applications, Laravel makes it easy to "broadcast" your events over a WebSocket connection. Broadcasting your Laravel... -
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PaaSTA
An open, distributed platform as a service
PaaSTA is a highly-available, distributed system for building, deploying, and running services using containers and Kubernetes. PaaSTA has been running production services at Yelp since 2016. It was originally designed to run on top of Apache Mesos but has subsequently been updated to use Kubernetes. Over time the features and functionality that PaaSTA provides have increased but the principal design remains the same. PaaSTA aims to take a declarative description of the services that teams... -
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ParallelStencil.jl
Package for writing high-level code for parallel stencil computations
ParallelStencil empowers domain scientists to write architecture-agnostic high-level code for parallel high-performance stencil computations on GPUs and CPUs. Performance similar to CUDA C / HIP can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl or AMDGPU.jl GPU Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding GPU Array...
